Mr. Shiyi Ren – Machine Learning  – Best Researcher Award

The University of Auckland  | New Zealand

Author Profile 

Early Academic Pursuits 🎓

Chengdu University (09/2014 – 06/2018)

Bachelor of Engineering in Vehicle Engineering

He began his academic journey at Chengdu University, where he pursued a Bachelor of Engineering in Vehicle Engineering. This foundational period was instrumental in shaping his technical skills and understanding of engineering principles. His undergraduate studies laid the groundwork for his future research endeavors, particularly in the fields of machine vision and robotics.

Sichuan Agricultural University (09/2018 – 06/2021)

Master of Agriculture in Agricultural Engineering and Information Technology

He continued his academic pursuits at Sichuan Agricultural University, earning a Master of Agriculture in Agricultural Engineering and Information Technology. His master’s research focused on the integration and demonstration of key technologies in the mechanization of potato production, specifically in hilly areas. This project (2018YFD0701103) involved the development and testing of a potato harvester, including the research of potato excavating parts, potato soil separation screens, and soil crushing rollers. This experience honed his skills in agricultural machinery and set the stage for his future research in mechatronics and automation.

 Professional Endeavors 💼

The University of Auckland (05/2022 – Present)

PhD Candidate of Mechatronics Engineering

Currently, he is a PhD candidate at The University of Auckland in the field of Mechatronics Engineering. His research focuses on advanced topics such as machine vision and deep learning. He is involved in pioneering projects, including the real-time prediction and measurement of the in vitro robotic food chewing process. His work aims to enhance the efficiency and accuracy of robotic systems through innovative technology integration.

Internship at CRRC Ziyang Co., Ltd (24/02/2020 – 26/03/2020)

Position: Crankshaft Engineer

During his internship at CRRC Ziyang Co., Ltd, Ren worked as a Crankshaft Engineer. He was responsible for the design of crankshafts, an experience that further solidified his practical engineering skills and his ability to apply theoretical knowledge in real-world industrial settings.

Contributions and Research Focus on Machine Learning 📚

His contributions to the field of engineering are substantial and varied. His research interests include machine vision, deep learning, and agricultural automation. His notable projects include:

  • Machine Vision and Deep Learning-Based Real-time Prediction and Measurement of the In Vitro Robotic Food Chewing Process (01/05/2018 – Present): This ongoing project aims to enhance the predictive capabilities of robotic systems using advanced machine vision and deep learning techniques.
  • Integration and Demonstration of Key Technologies in the Whole Mechanization of Potato Production on a Moderate Scale in Hilly Areas (2018YFD0701103) (01/09/2018 – 01/09/2022): This project focused on developing efficient and effective mechanized solutions for potato harvesting in challenging terrains.

Published Papers and Patents

  • Ren, S., Chen, B., Dhupia, J. S., Stommel, M., & Xu, W. (2023, October). “A Deep Learning System to Quantify and Predict the Chewing Process of Foods.” In ASME International Mechanical Engineering Congress and Exposition (Vol. 87639, p. V006T07A092). American Society of Mechanical Engineers.
  • Ren, S., Chen, B., Wang, X., Dhupia, J., Stommel, M., & Xu, W. (2023, November). “Concept of Real-Time Prediction and Evaluation System of Robotic Food Chewing Using Machine Vision and Deep Learning.” In 2023 29th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) (pp. 1-6). IEEE.
  • Zürn, M., Kienzlen, A., Klingel, L., Lechler, A., Verl, A., Ren, S., & Xu, W. (2023, August). “Deep Learning-Based Instance Segmentation for Feature Extraction of Branched Deformable Linear Objects for Robotic Manipulation.” In 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE) (pp. 1-6). IEEE.
  • Ren, S., Wu, X., Shi, D., Jikui, A., & Lv, X. “A Potato Earth Breaking Excavating Device” (Authorization Notice No.: CN 209489155 U).
  • Fu, Y., Ren, S. Y., Tang, P., Leng, Y. C., Chen, X. H., Tu, X. Y., & Lv, X. R. (2023). “Design and simulation test of digging device for small potato harvester.”
  • Wu, T., Zhang, Z., Ren, S., Guo, L., Zhang, Y., & Zeng, Y. (2023, November). “A Hybrid Evolutionary Algorithm for Stochastic Robot Disassembly Line Balancing Problem.” In 2023 29th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) (pp. 1-6). IEEE.
  • Tang, P., Ren, S., Jikui, A., Liu, Z., & Lv, X. (2021). “Design of a potato stubble cutting machine for side delivery.” In E3S Web of Conferences (Vol. 260, p. 03018). EDP Sciences.
  • Jikui, A., Lv, X., Ren, S., & Yang, H. (2019, April). “Design of hydraulic corn picking device.” In 2019 3rd International Forum on Environment, Materials and Energy (IFEME 2019) (pp. 130-133). Atlantis Press.

 Accolades and Recognition 🏆

His academic excellence has been recognized through several scholarships and awards:

  • 2nd-class scholarship (11/2018, 11/2019)
  • 3rd-class scholarship (11/2020)
  • 2nd Prize of Campus Integrity Culture Competition (10/2020)
  • China Scholarship Council (05/2022)

 Impact and Influence 🌍

His research has a significant impact on both the academic community and practical applications. His work in machine vision and deep learning for robotic systems contributes to advancements in automation technology, with potential applications in various industries, including agriculture and manufacturing. His contributions are particularly relevant in enhancing the efficiency and sustainability of agricultural practices.

 Legacy and Future Contributions 🔮

He is poised to leave a lasting legacy in the fields of mechatronics and agricultural engineering. His innovative research and practical contributions to mechanized systems and robotic technology pave the way for future advancements. As he continues his PhD at The University of Auckland, his ongoing projects and future endeavors are expected to further enhance the field and inspire future researchers and engineers.


Citations          3

h-index            1

i10-index         0

Notable Publications 

Shiyi Ren | Machine Learning | Best Researcher Award

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